Ai-Agent-Security

If you’re running AI agents in production and they have access to real tools — file systems, APIs, databases, external services — you have a security problem you may not have fully reckoned with yet. The problem: agents are not sandboxed by default. An agent that gets fed a malicious prompt (prompt injection), hallucinates a destructive command, or malfunctions can do real damage to your host system, your connected services, or your data. And most agent frameworks, even the good ones, don’t enforce OS-level isolation between the agent process and the machine it’s running on. ...

Two hours. That’s how long it took an autonomous AI agent to crack open McKinsey’s internal AI assistant and walk out with 46 million chat messages, 728,000 confidential client files, and 57,000 user account records — all in plaintext. The breach wasn’t carried out by a human hacker manually probing endpoints. It was executed by an offensive AI agent deployed by CodeWall, a red-team security startup, as part of an authorized penetration test. The agent operated autonomously: it selected the target, identified the attack surface, and executed the breach without human intervention beyond the initial launch. ...